The SM algorithmically accelerated dynamics can still overload users' cognitive capacities [1]}, [2]} and emotional state [3]}. Moreover, even providing contextual information and educational support together, they may not prevent students from compulsively seeking, producing and sharing harmful content that sometimes flows out of internet addiction [4]}, [5]}, [6]}. This raises a crucial question currently in the spotlight for SM platforms: How can the need to regulate the exposition and propagation of toxic social media content be balanced against other important factors such as rights to freedom of speech [7]}, [8]}?
In this regard, for the educationally managed community, the Companion targets together the cognitive, educational and technical social media threats implementing a hybrid regulation strategy combining self-regulation and soft automatic regulation strategies that we expect to be more effective than the two strategies separately.
The self-regulation aspect will build on education, and thus on the acquisition and use of new skills. As described above, using boosting as a behavioural intervention approach, through accurately developed educational activities proposed by the teachers, the students will improve their digital literacy about SM threats and ability to self regulate their interactions.
On the other side, the Collective well-being aware Recommender Systems (CWB-RS), will improve students’ CWB and support their experience by implementing soft automatic regulation adopting a nudging approach. This soft automatic regulation will be implemented through re-ranking and balancing threats, positive, a educational aspects of the content and connections originally proposed by the external social media recommender system.
